Staff Research Scientist, AI Agents & LLMs
Snowflake · US-WA-Bellevue
About this role
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset - who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. THE MISSION We are seeking a Staff Research Scientist to serve as a technical pillar within our AI research organization. You will not just execute on roadmaps - you will define them. At the intersection of autonomous agents and large language models (LLMs), you will build the models and systems that turn enterprise data into self-directed, decision-making agents - shifting from passive data access to autonomous execution. Our team operates at the frontier of enterprise AI, delivering both state-of-the-art models and production systems, including: - Arctic LLM: Enterprise foundation models optimized for performance and efficiency - Arctic-Text2SQL: Post-trained reasoning models with frontier-level quality at a fraction of cost and latency - Snowflake Intelligence: Brought research to production through agentic innovations in multi-step reasoning, Deep Research for structured and unstructured insights, and system optimization - Arctic Inference: High-performance LLM serving stack (Shift Parallelism, SwiftKV), open-sourced and powering Snowflake Cortex - Arctic Long-Context Training: Enables 1M+ token context training on a single H200 GPU - Agent World Models (AWM): RL training across 1,000+ synthetic environments for tool-using agents We focus on core challenges such as reli
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